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Chemical and Biological Technologies in Agriculture
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Insight into the key limiting factors affecting anaerobic fermentation quality and bacterial community of sweet sorghum by irradiation sterilization and microbiota transplant

Chemical and Biological Technologies in Agriculture volume 10, Article number: 17 (2023) Cite this article

Abstract

Biomass microbiota and chemical constituent are closely associated with final anaerobic fermentation performance. But the limiting factors affecting anaerobic fermentation quality and bacterial community have been rarely explored. This study aimed to elucidate the relative contribution of initial microbiota and chemical constituent of sweet sorghum on its final anaerobic fermentation quality. Sweet sorghum at two developmental stages (heading-stage, G1; hard-dough-stage, G2) was treated as follows: G1 microbiota + sterilized G1 (M1C1), G2 microbiota + sterilized G1 (M2C1), G1 microbiota + sterilized G2 (M1C2), and G2 microbiota + sterilized G2 (M2C2). The results showed that chemical constituent rather than microbiota changes remarkably influenced the production of lactic acid, propionic acid and ammonia-N, the relative abundance of Lactobacillus, Weissella, Lactococcus, Pediococcus, and Pantoea of sweet sorghum after anaerobic fermentation. The chemical constituent was the key limiting factor affecting the anaerobic fermentation quality of sweet sorghum. This study could provide a reference for clarifying the key limiting factors affecting anaerobic fermentation and making recommendations for production.

Graphical Abstract

Background

Sweet sorghum (Sorghum bicolor (L.) Moench) as a well-known forage or energy crop is widely planted in tropical, subtropical and temperate regions with humid, semi-humid and semi-arid climates due to its adaptable, fast-growing and high-yield properties [1]. It has been used in the production of sugar, food, fibrous products, biofuels and chemicals, especially feed. However, the toxic cyanogentic glycosides and antinutritional tannin in fresh sweet sorghum require anaerobic fermentation as the preferred processing method to degrade these components. Ensilage refers to the anaerobic fermentation of moist forages by epiphytic probiotics to produce mainly short-chain fatty acid (SCFA) from the sugars present [2]. However, it should be noted that when anaerobic fermentation is performed from forage harvested at different developmental stages, their fermentation patterns and final SCFA composition can be a far cry from. In the case of guinea grass, van Niekerk et al. [3] reported that the fermentation of guinea grass prepared at the early vegetative and boot stages was lactate-type, while the fermentation of guinea grass prepared at the full bloom stage was acetate type. These inconsistent results caused by developmental stages can ultimately be inferred from differences in the chemical and microbial compositions of forage at harvest. Namely, the developmental stage influences the phyllosphere microbiota and chemical constituent (including but not limited to dry matter (DM), water-soluble carbohydrates (WSC) and buffering capacity) of grasses, thereby affecting the final anaerobic fermentation quality. Therefore, it needs to clarify the relative contribution of initial phyllosphere microbiota and chemical constituent to final fermentation quality, which is of great significance for silage production.

Over the past 60 years, a series of research has tried to distinguish the role of chemical and microbial factors in the anaerobic fermentation quality. In order to suppress the disturbance of microbial factor, sterile material was gained through sterile cultivation [4], chemical sterilization [5], autoclaving [6], dry heat [7], etc. But the risk of chemical sterilization, performed by bactericides such as chloroform and toluene, limits its further application in related research. While the major challenge of sterile cultivation is the long-term maintenance of a totally sterile environment [4]. Although autoclaving and dry heat has desirable sterilization effects, they have been shown to cause significant changes in the physicochemical properties of forage [8]. Fortunately, γ-ray irradiation sterilization has recently been shown to disinfect forage material at appropriate doses without impacting plant enzyme activities and chemical constituent [9, 10], which is suitable for the preparation of sterile forage.

Microbiota transplantation, as the most effective method to reconstitute symbiotic microbiota, has been a prospective research tool in the field of medical and agricultural microecology [11]. Microbiota transplantation is not limited to the treatment of intestinal disease. Williams and Marco [12] assessed the feasibility of microbiota transplantation for phyllosphere microbial studies under laboratory conditions, and they found that it would be useful to elucidate the interactions of microbes on plants and important for agriculture and fermented food safety. These findings are also instructive for anaerobic fermentation studies. Mogodiniyai Kasmaei et al. [13] applied the microbiota transplant for the first time in anaerobic fermentation research and stated that the epiphytic microflora of forages can be transplanted effectively. In recent years, the next-generation sequencing (NGS) technique has been widely applied in sensitively and accurately monitoring microbial community succession, which makes it possible to evaluate the effects of phyllosphere microbiota and chemical constituent on microbial community structure and diversity.

Therefore, the current study was designed to elucidate the relative contribution of phyllosphere microbiota and chemical constituent to the anaerobic fermentation quality and bacterial community of sweet sorghum, which may be important in clarifying the key limiting factors affecting anaerobic fermentation and making recommendations for production.

Methods

Material preparation

Sweet sorghum was planted in the Baima National Agricultural-tech Zone (31° 61′ N, 119° 18′ E, a.s.l. 25.1 m, Jiangsu, China) on June 30, 2020. A 30 m2 planting field was separated into three equal blocks (for replications) and each block was further divided into two equal plots (two developmental stages). Half of the sweet sorghum was mowed on August 28, 2020, and the left sweet sorghum was mowed on October 2, 2020 to obtain two batches of sweet sorghum (G1, the heading stage; G2, the hard dough stage). The harvest time was in the morning with clear weather, and the stubble height was about 15 cm. Each batch of fresh sweet sorghum was immediately cut into about 2 cm lengths by a feed cutter, mixed totally and split into three parts for phyllosphere microbiota collection, fresh sample analysis and experimental preparation, respectively.

Phyllosphere microbiota collection

Following the procedures of Mogodiniyai Kasmaei et al. [13], the phyllosphere microbiota were respectively eluted from fresh G1 or G2, namely M1 or M2. Concretely, 5 kg fresh G1 or G2 was mixed thoroughly and separated into 10 portions (500 g per portion). Subsequently, 3 L Ringer solution (formula: NaCl, 2.25 g; KCl, 0.105 g; CaCl2, 0.06 g; NaHCO3, 0.05 g, dissolved in 1 L distilled water, adjusted to pH 6.9, sterilized by autoclaving at 121 °C for 15 min) containing 0.05% v/v Tween-80 was mixed with 500 g fresh-cut G1 or G2. Then, microbial suspension of the above mixture was obtained by shaking at 150 rpm for 2 min. After centrifuging at 16,000×g for 90 min at 4 °C, microbial precipitation was obtained and resuspended with 3 mL Ringer solution. Before the transplant, all microbial precipitation was pooled together and homogenized.

Experimental preparation and microbiota transplantation

After thorough mixing, about 450 g of fresh-cut G1 or G2 was loaded into each UV-sterilized laboratory silo (polythene bag with a size of 300 × 400 mm) and vacuum-sealed. Based on the dose and duration of irradiation sterilization recommended by Junges et al. [14], totally 18 laboratory silos (fresh material: 2 developmental stages × 3 replicates; anaerobic fermentation: 4 treatments × 3 replicates) were exposed to a Co-60 source and sterilized by γ-ray irradiation at 32 kGy for 4 h (Nanjing Xiyue Technology Co., Ltd, Jiangsu, China). Designate γ-ray sterilized G1 as C1 and γ-ray sterilized G2 as C2.

In an ultra-clean bench, the γ-ray sterilized silos were opened and treated as follows (Fig. 1): (i) transplantation of M1 to C1 (M1C1); (ii) transplantation of M2 to C1 (M2C1); (iii) transplantation of M1 to C2 (M1C2); and (iv) transplantation of M2 to C2 (M2C2). The transplant volume of M1 or M2 was 3 mL per silo and the silos were resealed and kept at the surrounding temperature (24 ± 4 ℃). Triplicate silos per treatment were opened and sampled after 30 days of anaerobic fermentation for further analyses. The experimental flow chart is shown in Fig. 2.

Fig. 1
figure 1

Experimental design diagram of this study. G1: fresh sweet sorghum harvested at the heading stage; G2: fresh sweet sorghum harvested at the hard dough stage; M1: phyllosphere microbiota eluted from sweet sorghum harvested at the heading stage; M2: phyllosphere microbiota eluted from sweet sorghum harvested at the hard dough stage; C1: irradiated sweet sorghum harvested at the heading stage; C2: irradiated sweet sorghum harvested at the hard dough stage

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Fig. 2
figure 2

Experimental flow chart of this study

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Chemical, microbial and fermentative parameter analyses

The chemical composition and microbial population were analyzed according to our previous study [15]. For fermentation parameter analysis, 30 g fresh or ensiled material was extracted with 90 mL deionized water at 4 °C for 24 h. After filtering with 4 layers of medical cheesecloth and Whatman filter paper, the pH of fresh or ensiled material was recorded by a HI 2221 pH/mV/°C bench meter (Hanna Instruments Inc., Rhode Island, United States) immediately. The ammonia-N (NH3-N) concentration of ensiled material was determined by colorimetry after a reaction with phenol and hypochloric acid [16]. The concentrations of ethanol and SCFA including lactic acid, acetic acid, propionic acid, n-butyric acid, and iso-butyric acid of ensiled material were determined by a 1260 Infinity II HPLC system (Agilent Technologies Inc., California, USA). The mobile phase was 2.5 mM H2SO4, the flow rate of the mobile phase was 0.5 mL/min and the column temperature was 55 °C. The concentration of butyric acid was the sum concentration of n-butyric acid and iso-butyric acid.

The NGS analyses

Preparatory work before sequencing (bacterial DNA extraction and PCR amplification) was performed following the procedures reported by Zhao et al. [17]. Purified amplicons (equimolar concentrations) were paired-end sequenced on a MiSeq PE300 platform (Illumina Inc., California, USA) provided by Majorbio Bio-Pharm Technology Co., Ltd. (Shanghai, China). The generated two sequencing files per replicate were first merged using FLASH (v1.2.11). Then, the obtained raw sequence data were quality filtered by QIIME (v1.9.1) to retain sequences with quality scores > 20. Operational taxonomic units (OTUs) were clustered with 97% identities using UPARSE (v7.0.0) and chimeric sequences were identified and removed using UCHIME (v4.1). After matching with the 132 SILVA database, the taxonomy of OTUs was assigned using RDP classifier (v2.11). Bacterial α-diversities (Shannon, Chao and Coverage indices) and Bray–Curtis metric β-diversity were calculated using QIIME (v1.9.1). Bray–Curtis distance metric nonmetric multidimensional scaling analysis (NMDS) plot was constructed using vegan R package (v4.1.2). Multispecies difference test histograms at the top 10 genera between treatments were constructed using STAMP (v2.1.3) to figure out the bacterial abundance differences.

Statistical analysis

The GLM of SAS (v9.2; SAS Institute Inc., North Carolina, USA) was applied to investigate the effects of irradiation sterilization, developmental stage and their interactions on the physio-biochemical characteristics, as well as the effects of phyllosphere microbiota, chemical constituent and their interactions on the fermentation parameters and bacterial α-diversities in a 2 × 2 factorial design.

The statistical model for Table 1 was as follows:

Table 1 The phyllosphere characteristics of fresh sweet sorghum
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$${Y}_{ij}=\mu +{\gamma }_{i}+{D}_{j}+{(\gamma \times D)}_{ij}+{e}_{ijk}$$

where Yij is the dependent variable; μ is the overall mean; γi is the effect of irradiation sterilization (i = 2, with vs. without); Dj is the effect of developmental stage (j = 2, G1 vs. G2); (γ × D)ij are the interaction effects of irradiation sterilization and developmental stage; and eijk is the residual error.

The model for Tables 2 and 3 was as follows:

Table 2 Effects of phyllosphere microbiota and chemical constituent on anaerobic fermentation quality and SCFA production
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Table 3 Effect of phyllosphere microbiota and chemical constituent on diversity and richness indices of the bacterial community
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$${Y}_{ij}=\mu +{C}_{i}+{M}_{j}+{(C\times M)}_{ij}+{e}_{ijk}$$

where Yij is the dependent variable; μ is the overall mean; Ci is the effect of chemical constituent (i = 2, C1 vs. C2); Mj is the effect of phyllosphere microbiota (j = 2, M1 vs. M2); (C × M)ij are the interaction effects of chemical constituent and phyllosphere microbiota; and eijk is the residual error. The difference compared between treatments was performed using student t-test when the effects of phyllosphere microbiota or chemical constituent were significant. Means were statistically different at P < 0.05.

Results

Phyllosphere characteristics of fresh sweet sorghum

Different from that the developmental stage had significant (P < 0.001) effects on both phyllosphere chemical and microbial parameters, irradiation sterilization had no effects (P > 0.05) on the chemical constituent of sweet sorghum (Table 1 and Additional file 1). As sweet sorghum grew, pH value, DM, WSC, neutral detergent fiber (NDF) and acid detergent fiber (ADF) content as well as lactic acid bacteria (LAB), aerobic bacteria, yeast, moulds and enterobacteria number significantly (P < 0.001) increased, whereas CP content and buffering capacity significantly (P < 0.001) decreased. There were no colonies found in the irradiated sweet sorghum through the culture-based method.

Chemical and fermentation parameters

As shown in Table 2, changes in the chemical constituent significantly (P < 0.05) impacted the value of pH, the content of DM and WSC, the concentrations of lactic acid, acetic acid, propionic acid and SCFA, the lactic acid–acetic acid ratio and the number of LAB and yeast, while changes of the phyllosphere microbiota significantly (P < 0.05) impacted the acetic acid concentration and the lactic acid–acetic acid ratio. Concretely, M1C2 and M2C2 contained higher (P < 0.05) levels of DM, WSC, lactic acid, SCFA, lactic acid–acetic acid ratio and NH3–N, and lower (P < 0.05) levels of pH and yeast than M1C1 and M2C1. Compared with the M1 transplant, the M2 transplant increased the concentration of acetic acid and decreased the lactic acid–acetic acid ratio (P < 0.05). No or negligible (< 2.0 log10 colony-forming units (cfu)/g fresh weight (FW)) aerobic bacteria, yeast and enterobacteria were detected in all treatments.

Bacterial community structure and diversity

After NGS, 1,139,144 raw sequences were formed from 6 fresh materials and 12 ensiled materials (Table 3). Totally 645,156 quality sequences were got by quality filtering and subsequently clustered into 640 OTUs according to the 97% sequence identity threshold. The changes in chemical constituent significantly (P < 0.05) influenced OTUs number and Shannon and Chao1 indices; differently, the changes in phyllosphere microbiota did not influence (P > 0.05) these α-diversity parameters. The indices of Shannon and Chao1 were peak in fresh material (phyllosphere microbiota) and followed by ensiled material. After 30-day anaerobic fermentation, M1C2 detected the lowest OTUs number and Shannon and Chao1 indices. The Coverage index of all sequenced samples was above 0.99.

The differences of bacterial β-diversity among treatments are shown in Fig. 3. A clear separation was observed between the sample points of the fresh and ensiled sample. Wherein the sample points of M1 and M2 were well separated, the sample points of M1C1 and M2C1 were slightly separated from those of M1C2 and M2C2.

Fig. 3
figure 3

Nonmetric multidimensional scaling (NMDS) plot based on the Bray–Curtis distance metric of bacterial community at genus level between samples (2D stress = 0.05). M1: phyllosphere microbiota eluted from sweet sorghum harvested at the heading stage; M2: phyllosphere microbiota eluted from sweet sorghum harvested at the hard dough stage; C1: irradiated sweet sorghum harvested at the heading stage; C2: irradiated sweet sorghum harvested at the hard dough stage; M1C1: transplantation of M1 to C1; M2C1: transplantation of M2 to C1; M1C2: transplantation of M1 to C2; M2C2: transplantation of M2 to C2

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Figure 4 shows that Proteobacteria (72.6%), Firmicutes (10.9%) and Actinobacteriota (10.2%) were the phyla with high relative abundance (RA) in M1, while Proteobacteria (80.9%) and Bacteroidota (8.60%) were the phyla with high RA in M2. With the growth of sweet sorghum, the RA of Firmicutes and Actinobacteriota decreased from 10.9% and 10.2% to 4.21% and 5.53%, respectively, but the RA of Proteobacteria and Bacteroidota increased from 72.6 and 5.86% to 80.9% and 8.60%, respectively. After 30-day anaerobic fermentation, Firmicutes (> 95%) were the overwhelmingly dominant phylum in all the microbial communities.

Fig. 4
figure 4

Effect of phyllosphere microbiota and chemical constituent on the RA (%) of bacterial community at the phylum level in fresh and ensiled sweet sorghum. M1: phyllosphere microbiota eluted from sweet sorghum harvested at the heading stage; M2: phyllosphere microbiota eluted from sweet sorghum harvested at the hard dough stage; C1: irradiated sweet sorghum harvested at the heading stage; C2: irradiated sweet sorghum harvested at the hard dough stage; M1C1: transplantation of M1 to C1; M2C1: transplantation of M2 to C1; M1C2: transplantation of M1 to C2; M2C2: transplantation of M2 to C2

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There were 21 and 14 genera with an RA greater than 1% in M1 and M2, respectively (Fig. 5). The most abundant genera in M1 were Acinetobacter (20.4%), followed by Sphingomonas (10.9%), Pseudomonas (9.20%) and Microbacterium (8.77%), while Pantoea (28.8%) and Enterobacter (24.7%) were 2 genera with high abundance in M2. As anaerobic fermentation proceeded, the original bacterial community of sweet sorghum was rapidly replaced by Lactobacillus and Weissella. The changes in chemical constituent significantly (P < 0.05) impacted the RA of Lactobacillus, Weissella, Lactococcus and Pediococcus in M1C1 and M1C2, and Lactobacillus, Weissella, Leuconostoc and Pantoea in M2C1 and M2C2 (Fig. 6A and B). While the changes in phyllosphere microbiota only impacted (P < 0.05) the RA of Weissella in M1C1 and M2C1 as well as in M1C2 and M2C2 (Fig. 6C and D).

Fig. 5
figure 5

Effect of phyllosphere microbiota and chemical constituent on the RA (%) of bacterial community at the genus level in fresh and ensiled sweet sorghum. M1: phyllosphere microbiota eluted from sweet sorghum harvested at the heading stage; M2: phyllosphere microbiota eluted from sweet sorghum harvested at the hard dough stage; C1: irradiated sweet sorghum harvested at the heading stage; C2: irradiated sweet sorghum harvested at the hard dough stage; M1C1: transplantation of M1 to C1; M2C1: transplantation of M2 to C1; M1C2: transplantation of M1 to C2; M2C2: transplantation of M2 to C2

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Fig. 6
figure 6

Differential analyses bar plots at the genus level (top 10 genera) between treatments. * = 0.01 < P ≤ 0.05; ** = 0.001 < P ≤ 0.01. M1: phyllosphere microbiota eluted from sweet sorghum harvested at the heading stage; M2: phyllosphere microbiota eluted from sweet sorghum harvested at the hard dough stage; C1: irradiated sweet sorghum harvested at the heading stage; C2: irradiated sweet sorghum harvested at the hard dough stage; M1C1: transplantation of M1 to C1; M2C1: transplantation of M2 to C1; M1C2: transplantation of M1 to C2; M2C2: transplantation of M2 to C2

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Discussion

Effects of irradiation sterilization and developmental stage on the chemical constituent and phyllosphere microbiota of fresh sweet sorghum

There were no distinct differences in chemical constituent between fresh and irradiated samples, and γ-ray irradiation at the dose of 32 kGy effectively sterilized forage grass because no microorganisms were cultured from the irradiated sweet sorghum, which was similar to previous studies [18, 19]. Comino et al. [20] found that forage maturity greatly influenced its chemical and microbial characteristics. In the current study, DM, WSC, NDF and ADF content increased while CP content decreased as sweet sorghum grew, which was possibly due to the increase of cell wall deposition and the decline of leaf-stem ratio [21]. The decrease in the CP content might in turn explain the decrease in BC as the CP content of materials is positively correlated with BC [22].

Throughout the growth cycle of forage, the external environment (e.g., solar radiation, temperature and rainfall) and internal environment (e.g., plant morphology, moisture content and leaf thickness) are changing, and they are reported to affect microbial colonization [23]. The number of LAB, aerobic bacteria, yeast and enterobacteria as well as the α-diversities of phyllosphere microbiota in this study increased with the maturity of sweet sorghum, which further confirmed the fact that the microbial number and diversity of phyllosphere can be sharply influenced by the developmental stages. This phenomenon can be partly explained by the increased WSC content and aging tissue proportion of sweet sorghum from the heading stage to the hard dough stage. Recent studies showed that sugar and volatile organic compounds secreted by forage play an important role in determining the microbial population of forage [24, 25]. Microbes are known to enrich on sugar-rich plants such as maize. Moreover, as Thompson et al. [26] reported, the nutrients such as sugar released from aging tissue and leaves were found to benefit the growth of phyllosphere microorganisms.

Effects of phyllosphere microbiota and chemical constituent on the anaerobic fermentation quality

Regardless of developmental stage, the anaerobic fermentation of sweet sorghum displayed desirable homolactic fermentation, reflected in low pH values (< 4.0) and high lactic acid-acetic acid ratio [27]. The higher DM content of M1C2 and M2C2 (C2 anaerobic fermentation) than that of M1C1 and M2C1 (C1 anaerobic fermentation) was associated with the higher DM content in C2 than that in C1. Likewise, the higher WSC content, lactic acid concentration and SCFA production in M1C2 and M2C2 than those in M1C1 and M2C1 could ascribe to the higher WSC content in C2 than that in C1. The acetic acid concentration of M1C1 and M2C1 was higher than that of M1C2 and M2C2. Meanwhile, a higher acetic acid concentration was also observed in M2C1 and M2C2 (M2 transplant). These results suggested that the acetic acid generation of sweet sorghum after anaerobic fermentation in this study was associated with the chemical constituent and phyllosphere microbiota of sweet sorghum at harvest. This is not difficult to understand because the acetic acid in desirable anaerobic fermentation is mainly driven by the fermentation of pentose and heterofermentative LAB. Pentose fermentation converts pentose to the intermediate of d-xylose-5-phosphate and then to lactic acid and acetic acid [22]. Although the data of pentose were not shown in this study, the higher abundance of Leuconostoc in M2C1 and M2C2 (M2 transplant) still partly explained the higher acetic acid generation because Leuconostoc are heterofermentative LAB [28].

Benefiting from homolactic fermentation, the NH3-N level in all treatments was below the maximum acceptable limit (100 g/kg TN) [22]. The protein degradation and NH3-N formation during anaerobic fermentation are a complex biochemical process, involving the activities of plant protease, clostridia, enterobacteria, etc. Regardless of phyllosphere microbiota, the NH3-N concentration of M1C2 and M2C2 was always higher than that of M1C1 and M2C1, which was in line with the finding of Jia et al. [29] that the silage produced by more mature whole-crop oat had higher NH3–N concentration. The higher proteolysis degree at the mature stage reported by Faria et al. [30] probably explained the above higher NH3–N concentration. As O2 is depleted, the number of aerobic bacteria and moulds that cannot tolerate anaerobic conditions rapidly decreased to a negligible level [31]. While the undetected or negligible number of enterobacteria in all treatments was associated with the low pH value. Although yeasts are resistant to low pH, SCFA such as lactic acid and acetic acid can pass through the yeast cell membrane in the form of non-dissociation and release H+ to reduce intracellular acidity, finally suppress or kill the yeast [22]. Correspondingly, the higher concentrations of SCFA in M1C2 and M2C2 were accompanied by the lower number of yeasts.

Different from the acetic acid concentration, which was impacted by both chemical constituent and phyllosphere microbiota changes, other fermentation parameters such as pH, lactic acid, propionic acid, SCFA and NH3-N were only impacted by the chemical constituent changes.

Effects of phyllosphere microbiota and chemical constituent on the bacterial community structure and diversity

All coverage indices were above 99%, implying that most of the bacterial community had been fully captured. And the number of OTUs in M2 was higher than that in M1, suggesting that the bacterial composition in G2 was more complex and abundant. Anaerobic fermentation process decreased the species richness and diversity of the bacterial community, reflected by the reduced Shannon and Chao1 indices, and this could be associated with the disappearance of acid-intolerant aerobes [32]. Low pH conditions are mainly responsible for the reduced microbial diversity in acidic habitats [33], which could in turn explain the lowest Shannon and Chao1 indices in M1C2 with the lowest pH value.

According to Shannon and Chao1 indices, changes in chemical constituent rather than phyllosphere microbiota remarkably affected both the bacterial richness and diversity of sweet sorghum after anaerobic fermentation. This indicated that the difference in bacterial α-diversities in this study mainly resulted from the chemical constituent changes of fresh sweet sorghum at harvest. The Shannon and Chao1 indices of M1C2 and M2C2 were lower than those of M1C1 and M2C1, which could be explained by the superiority of C2. The lower buffering capacity and higher WSC content of C2 stimulated the proliferation of LAB, accelerated the initial LA production and acidification, thereby further decreasing the α-diversities of the bacterial community.

The clear separation of sample points M1 and M2 in the NMDS plot showed great differences in the composition of bacterial community for fresh sweet sorghum at two developmental stages, and this could be associated with climate, the physio-biochemical characteristics of forage grass, or other factors [19]. Meanwhile, the separated clustering between the fresh and ensiled sample was as abovementioned attributed to the disappearance of acid- and anaerobic-intolerant phyllosphere bacteria during anaerobic fermentation. The sample points of M1C1 and M2C1 or M1C2 and M2C2 were clumped together, suggesting that the composition of the bacterial community was similar in C1 or C2 anaerobic fermentation.

Proteobacteria dominated the phyllosphere microbiota of fresh sweet sorghum (M1 and M2), while Firmicutes were the overwhelmingly dominant phylum after anaerobic fermentation. The succession from Proteobacteria to Firmicutes under anaerobic environments has been extensively documented [8, 17, 18, 34,35,36]. The anaerobic fermentation process benefited the growth of Firmicutes because this phylum preferred the anaerobic and acid environments [37]. The apparent succession of bacterial community from Proteobacteria to Firmicutes after anaerobic fermentation could ascribe to the inhibition of aerobic genera (Acinetobacter, Sphingomonas, Pseudomonas, etc.) and the bloom of LAB (Lactobacillus, Weissella, Pediococcus, etc.). Lactobacillus, Weissella and Pediococcus are the 3 most common genera in silages [38, 39]. Weissella and Pediococcus are generally considered early colonizers during ensiling [34, 40] due to their weaker tolerance to acid compared with Lactobacillus [41,42,43]. The initial acid environment established by Pediococcus and Weissella is suitable for the growth of Lactobacillus [44]. Thus, Lactobacillus dominated the bacterial community of sweet sorghum after anaerobic fermentation, followed by Weissella and Pediococcus.

To clearly elucidate the relative contribution of chemical constituent and phyllosphere microbiota on the bacterial community of sweet sorghum after anaerobic fermentation, the multispecies difference test was used to show the differences of bacterial community composition between treatments. Chemical constituent changes have a significant impact on the RA of Lactobacillus, Weissella, Lactococcus, Pediococcus, Leuconostoc and Pantoea, while phyllosphere microbiota changes only impacted the RA of Leuconostoc in sweet sorghum after anaerobic fermentation. Lin et al. [45] analyzed the bacterial population of alfalfa and maize before and after ensiling and found that the epiphytic microbiota could not predict the final fermentation outcome due to the chemical constituent (WSC, BC, etc.) differences of fresh material. A similar finding was also obtained in the current study, that is, the differences in the anaerobic fermentation quality, SCFA production and bacterial community of sweet sorghum harvested at various developmental stages were primarily attributed to different chemical constituents at harvest. This study may provide the first record for further understanding the relative contribution of chemical and microbial factors to the bacterial community and anaerobic fermentation quality of sweet sorghum, which can guide subsequent production practices to regulate anaerobic fermentation and improve silage production. The main limitation of the present study is the failure to trace down the microbial community to the species level using third-generation sequencing, which needs to be addressed in future studies (Additional file 1).

Conclusions

In the current study, the chemical constituent changes had remarkable effects on the concentration of lactic acid, acetic acid, propionic acid and NH3-N as well as the RA of Lactobacillus, Weissella, Lactococcus, Pediococcus, Leuconostoc and Pantoea. While the phyllosphere microbiota changes only affected the concentration of acetic acid and the RA of Leuconostoc. Thus, the differences in the bacterial community and anaerobic fermentation quality of sweet sorghum at the two developmental stages were primarily driven by the chemical factors at harvest. The selection and breeding of new varieties of sweet sorghum for anaerobic fermentation may pay more attention to the improvement of chemical and nutritional parameters. Certainly, future work is required to further verify the findings of this study.

Availability of data and materials

All data generated or analyzed during this study are included in this published article.

Abbreviations

ADF:

Acid detergent fiber

C:

The effect of chemical constituent, C1 vs. C2

C1 :

Irradiated sweet sorghum harvested at the heading stage

C2 :

Irradiated sweet sorghum harvested at the hard dough stage

C × M:

The interaction between chemical constituent and phyllosphere microbiota

cfu:

Colony-forming units

CP:

Crude protein

DM:

Dry matter

FW:

Fresh weight

G1 :

Fresh sweet sorghum harvested at the heading stage

G2 :

Fresh sweet sorghum harvested at the hard dough stage

LAB:

Lactic acid bacteria

M:

The effect of phyllosphere microbiota, M1 vs. M2

M1 :

Phyllosphere microbiota eluted from sweet sorghum harvested at the heading stage

M2 :

Phyllosphere microbiota eluted from sweet sorghum harvested at the hard dough stage

NDF:

Neutral detergent fiber

NGS:

Next-generation sequencing

NH3-N:

Ammonia nitrogen

NMDS:

Nonmetric multidimensional scaling analysis

OTUs:

Operational taxonomic units

RA:

Relative abundance

RDP:

Ribosomal database project

SCFA:

Short-chain fatty acid

TN:

Total nitrogen

WSC:

Water-soluble carbohydrates

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Acknowledgements

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Funding

This work was financially supported by the NSFC (Grant No. 32201464), Jiangsu Funding Program for Excellent Postdoctoral Talent (Grant No. 2022ZB319) and United Fund for Regional Inno & Dev of NSFC (Grant No. U20A2003).

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Authors and Affiliations

  1. Institute of Ensiling and Processing of Grass, College of Agro-Grassland Science, Nanjing Agricultural University, Nanjing, 210095, People’s Republic of China

    Jie Zhao, Zhao-Di Jing, Xue-Jing Yin, Jun-Feng Li, Zhi-Hao Dong, Si-Ran Wang & Tao Shao

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  1. Jie Zhao
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Contributions

JZ: methodology, formal analysis, visualization, writing-original draft preparation. ZJ and XY: validation, methodology, software. JL: investigation, formal analysis. SW and ZD: methodology, visualization. TS: conceptualization, project administration, resources, data curation, supervision, funding acquisition, writing—review and editing. All authors read and approved the final manuscript.

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Correspondence to Tao Shao.

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Supplementary Information

Additional file 1: Table S1.

The chemical, microbial and fermentative parameters of sweet sorghum (untreated) after 30 days of anaerobic fermentation. Table S2. The chemical, microbial and fermentative parameters of sweet sorghum (irradiated) after 30 days of anaerobic fermentation.

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Zhao, J., Jing, ZD., Yin, XJ. et al. Insight into the key limiting factors affecting anaerobic fermentation quality and bacterial community of sweet sorghum by irradiation sterilization and microbiota transplant. Chem. Biol. Technol. Agric. 10, 17 (2023). https://doi.org/10.1186/s40538-023-00392-w

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